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Journal articles on the topic 'Mobile networks'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 May 2024

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1

S, Durga Devi, and Mythrae R. "The Mathematics of Mobile Networks." International Journal of Trend in Scientific Research and Development Volume-3, Issue-2 (February 28, 2019): 795–97. http://dx.doi.org/10.31142/ijtsrd21492.

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Ray, Shweta. "Intelligent-Driven Green Resource Allocation for Industrial Internet of Things In 5g Heterogeneous Network." International Journal for Research in Applied Science and Engineering Technology 10, no. 7 (July 31, 2022): 55–67. http://dx.doi.org/10.22214/ijraset.2022.45161.

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Abstract: Mobile networks' energy consumption is rising in tandem with the volume of traffic and the number of people utilising mobile technology. To maintain the long-term survival of the next generation of mobile networks, there must be an emphasis on energy efficiency. By minimising the network's power consumption and proposing an energy-efficient network architecture, this thesis addresses the issue of increasing 5G and beyond network efficiency. The first component of this thesis focuses on base stations (BSs), the most energy-intensive part of mobile networks. Mobile network providers offer us with a data set that contains information on the amount of traffic on their system. The poor temporal granularity of mobile network traffic data makes it difficult to train ML systems for sleep mode management choices. Bursty arrivals are taken into consideration while generating mobile network traffic statistics.

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Zavlanos, Michael M., Alejandro Ribeiro, and George J. Pappas. "Network Integrity in Mobile Robotic Networks." IEEE Transactions on Automatic Control 58, no. 1 (January 2013): 3–18. http://dx.doi.org/10.1109/tac.2012.2203215.

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4

Kwun Han and S. Ghosh. "Going mobile [mobile-computing networks]." IEEE Circuits and Devices Magazine 14, no. 1 (1998): 10–22. http://dx.doi.org/10.1109/101.648595.

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Fu Jie Tey, Fu Jie Tey, Tin-Yu Wu Fu Jie Tey, Yueh Wu Tin-Yu Wu, and Jiann-Liang Chen Yueh Wu. "Generative Adversarial Network for Simulation of Load Balancing Optimization in Mobile Networks." 網際網路技術學刊 23, no. 2 (March 2022): 297–304. http://dx.doi.org/10.53106/160792642022032302010.

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<p>The commercial operation of 5G networks is almost ready to be launched, but problems related to wireless environment, load balancing for example, remain. Many load balancing methods have been proposed, but they were implemented in simulation environments that greatly differ from 5G networks. Current load balancing algorithms, on the other hand, focus on the selection of appropriate Wi-Fi or macro & small cells for Device to Device (D2D) communications, but Wi-Fi facilities and small cells are not available all the time. For this reason, we propose to use the macro cells that provide large coverage to achieve load balancing. By combing Generative Adversarial Network (GAN) with the ns-3 network simulator, this paper uses neural networks in TensorFlow to optimize load balancing of mobile networks, increase the data throughput and reduce the packet loss rate. In addition, to discuss the load balancing problem, we take the data produced by the ns-3 network simulator as the real data for GAN.</p> <p> </p>

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Nada, Fayza A. "Steady State Analysis of Base Station Buffer Occupancy in a Cellular Mobile System." Journal of Computer Networks and Communications 2023 (March 23, 2023): 1–13. http://dx.doi.org/10.1155/2023/1364824.

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The 3rd generation partnership project (3GPP) standards organizations makes great efforts in order to reduce the latency of 5G mobile networks to the least possible extent. Recently, these networks are associated with big buffers to maximize the network utilization and minimize the wasted wireless resources. However, in existence of the TCP congestions, having bottlenecks are still expected on radio access networks (RANs) data paths. Consequently, this influences the network performance and reduces its quality of services (QoSs). Apparently, studying and improving the behavior of buffers deployed at 5G mobile networks devices can contribute to solving these problems (at least by reducing the queuing time at these buffers). In this paper, we study the buffer behavior of base stations in a 5G mobile network at steady state. We consider a cellular mobile network consisting of finite number of users (stations, terminals, and mobiles). At any time-slot, a station may be using the channel (busy) or not using the channel (idle). Since system analysis of cellular mobile networks in general form is rather complex, solutions are always obtained in closed forms or by numerical techniques. A two-dimensional traffic system for cellular mobile networks is presented, and the main performance evaluations are derived. Moreover, different moments of the base station buffer occupancy are calculated. The study reveals that there is a correlation between the state of the mobile stations (busy or idle) and the expected buffers occupancy of the base station. In addition, the results discussions demonstrate some important factors and parameters that affect the base station buffers and the overall network performance. These factors can be further worked on and controlled to obtain the least possible latency in next generation mobile networks.

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Mohan, Seshadri, Nitin Agarwal, and Ashutosh Dutta. "Social networks meet mobile networks." IEEE Communications Magazine 50, no. 6 (June 2012): 72–73. http://dx.doi.org/10.1109/mcom.2012.6211488.

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Sugumaran, Vijayan, Shriram Raghunathan, and K. Vivekanandan. "Mobile Community Networks." International Journal of Mobile Computing and Multimedia Communications 1, no. 2 (April 2009): 61–79. http://dx.doi.org/10.4018/jmcmc.2009040105.

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Wang, You-Chiun. "Mobile Sensor Networks." ACM Computing Surveys 47, no. 1 (July 2014): 1–36. http://dx.doi.org/10.1145/2617662.

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Campbell, Andrew T., Michael E. Kounavis, and Raymond R. F. Liao. "Programmable mobile networks." Computer Networks 31, no. 7 (April 1999): 741–65. http://dx.doi.org/10.1016/s0169-7552(98)00298-0.

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Sheng-Yuan Tu and Ali H. Sayed. "Mobile Adaptive Networks." IEEE Journal of Selected Topics in Signal Processing 5, no. 4 (August 2011): 649–64. http://dx.doi.org/10.1109/jstsp.2011.2125943.

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Irvine, J. M., I. S. Groves, and R. Tafazolli. "Future mobile networks." Electronics & Communication Engineering Journal 12, no. 6 (December 1, 2000): 262–70. http://dx.doi.org/10.1049/ecej:20000604.

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Hadžić, Anesa, and Goran Popović. "6G - SIXTH GENERATION MOBILE NETWORKS." Nauka i tehnologija 11, no. 1 (June 30, 2023): 1–7. http://dx.doi.org/10.58952/nit20231101001.

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<p style="text-align: justify;">In this paper, we will present mobile networks of the sixth generation, popularly called 6G. It is expected that this generation of mobile networks will cause a complete revolution in the world of technology but also the daily life of the people who use it. The 6G mobile network will not only be a continuation of the 5G mobile network, but will represent a completely new concept of integration of all existing and future segments of the idea of global networking. 6G networks are expected to reach significantly higher levels of heterogeneity than their predecessors and to support applications that are far more advanced than current mobile usage scenarios, such as virtual and augmented reality (VR/AR), ubiquitous instant communications, ubiquitous intelligence and Internet of Things (IoT). 6G should enable the full integration of wireless networks based on different technologies. A significant advantage of the 6G mobile network that will enable this is certainly the data rate, which will reach speeds of even 1TB/s. In addition, 6G mobile networks will enable extremely high coverage, negligible delay, high reliability and availability in almost all rural areas.</p>

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Guo, Zhaoming, Shihua Bi, Yi Jiang, and Zheren Long. "Mobile Network Computers Should be the Terminal of Mobile Communication Networks." Wireless Personal Communications 85, no. 4 (July 15, 2015): 1895–904. http://dx.doi.org/10.1007/s11277-015-2878-0.

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Borawake-Satao, Rachana, and Rajesh Shardanand Prasad. "Mobile Sink with Mobile Agents." International Journal of Rough Sets and Data Analysis 4, no. 2 (April 2017): 24–35. http://dx.doi.org/10.4018/ijrsda.2017040102.

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Wireless Sensor Networks (WSN) has been drawing considerable attention and discussion in recent years due to its potential applications in various fields. In modern applications for future internet the MSN (Mobile Sensor Network) is a key factor. Mobility allows the applications of Wireless Sensor Network to be compatible with IoT (Internet of Things) applications. As mobility enhances capability of the network it also affects the performance of the network at each layer. In recent years the various methodologies are proposed to handle mobility. Most of them use mobility for efficient data collection in WSNs. The purpose of this paper is to study effects of mobility on various performance parameters of the network and to explore the effective techniques to handle mobility in network. This paper proposes Mobile Sink with Mobile Agent mobility model for WSN which will increase the lifetime of the network using sink and agent node mobility.

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Palackal, Antony, Paul Nyaga Mbatia, Dan-Bright Dzorgbo, Ricardo B. Duque, Marcus Antonius Ynalvez, and Wesley M. Shrum. "Are mobile phones changing social networks? A longitudinal study of core networks in Kerala." New Media & Society 13, no. 3 (March 11, 2011): 391–410. http://dx.doi.org/10.1177/1461444810393900.

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Mobile telephony has diffused more rapidly than any Indian technology in recent memory, yet systematic studies of its impact are rare, focusing on technological rather than social change. We employ network surveys of separate groups of Kerala residents in 2002 and again in 2007 to examine recent shifts in mobile usage patterns and social relationships. Results show (1) near saturation of mobiles among both the professionals and nonprofessionals sampled, (2) a decrease in the number of social linkages across tie types and physical locations, and (3) a shift towards friends and family but away from work relationships in the core networks of Malayalis. We interpret these findings as support for the bounded solidarity thesis of remote communication that emphasizes social insulation and network closure as mobiles shield individuals from their wider surroundings.

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Alrashed, Ebrahim A., and Mehmet Hakan Karaata. "Imposter Detection in Mobile Wireless Sensor Networks." International Journal of Computer and Communication Engineering 3, no. 6 (2014): 434–41. http://dx.doi.org/10.7763/ijcce.2014.v3.364.

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Chen, Hsing-Chung, Marsha Violetta, Chien-Erh Weng, and Tzu-Liang Kung. "Cognitive RBAC in mobile heterogeneous networks." Computer Science and Information Systems 10, no. 2 (2013): 779–806. http://dx.doi.org/10.2298/csis121110034c.

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In communication networks, a cognitive network (CN) is a new type of data network which is used to solve some of the problems that face current networks. Cognitive radio (CR) is part of a cognitive network and a smart wireless communication system. CR is conscious of its surrounding environment, and learns from the environment. It adapts its internal states by making corresponding real-time changes in certain operating parameters. In this paper, we propose a novel Cognitive RBAC (Role-Based Access Control) scheme which can be applied to Mobile Heterogeneous Networks (MHNs). The MHNs consist of mobile communication systems and Wi-Fi systems. The required new definitions for the RBAC model are proposed in this paper. They can improve the ability of conventional RBAC model to meet new challenges. In our scheme, we assume that a Cognitive Server (CS) provides and manages the permissions of services, and Network Providers support and manage a variety CRs and CNs, individually. For more efficiently managing CR and CN and meeting the large scale heterogeneous networks, we let mobile user can perceive network candidate actively to access services, in which the permissions are depending to the contract made by CS with each Network Provider. In this paper, the new generalized cognitive RBAC model and their definitions are proposed, and could be applied to new applications in a MHNs environment.

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Dr.R., Udayakumar, Dr Suvarna Yogesh Pansambal, Dr Yogesh Manohar Gajmal, Vimal Dr.V.R., and Sugumar Dr.R. "User Activity Analysis Via Network Traffic Using DNN and Optimized Federated Learning based Privacy Preserving Method in Mobile Wireless Networks." Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications 14, no. 2 (June 30, 2023): 66–81. http://dx.doi.org/10.58346/jowua.2023.i2.006.

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Mobile and wireless networking infrastructures are facing unprecedented loads due to increasing apps and services on mobiles. Hence, 5G systems have been developed to maximise mobile user experiences as they can accommodate large volumes of traffics with extractions of fine-grained data while offering flexible network resource controls. Potential solutions for managing networks and their security using network traffic are based on UAA (User Activity Analysis). DLTs (Deep Learning Techniques) have been recently used in network traffic analysis for better performances. These previously suggested techniques for network traffic analysis typically need voluminous information on network usages. Hence, this work proposes OFedeMWOUAA (optimal federated learning-based UAA technique with Meadow Wolf Optimisation) and DNN (deep Neuron Networks) for minimizing risks of data leakages in MWNs (Mobile Wireless Networks). In the proposed OFedeMWOUAA, the need to submit data to cloud servers does not arise because it trains DLTs locally and only uploads model gradients or knowledge weights. The OFedeMWOUAA approach effectively decreases dangers to data privacies with very minor performance losses in simulations.

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Zhao, Dawei, Haipeng Peng, Lixiang Li, Yixian Yang, and Shudong Li. "An Efficient Patch Dissemination Strategy for Mobile Networks." Mathematical Problems in Engineering 2013 (2013): 1–13. http://dx.doi.org/10.1155/2013/896187.

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Mobile phones and personal digital assistants are becoming increasingly important in our daily life since they enable us to access a large variety of ubiquitous services. Mobile networks, formed by the connection of mobile devices following some relationships among mobile users, provide good platforms for mobile virus spread. Quick and efficient security patch dissemination strategy is necessary for the update of antivirus software so that it can detect mobile virus, especially the new virus under the wireless mobile network environment with limited bandwidth which is also large scale, decentralized, dynamically evolving, and of unknown network topology. In this paper, we propose an efficient semi autonomy-oriented computing (SAOC) based patch dissemination strategy to restrain the mobile virus. In this strategy, some entities are deployed in a mobile network to search for mobile devices according to some specific rules and with the assistance of a center. Through experiments involving both real-world networks and dynamically evolving networks, we demonstrate that the proposed strategy can effectively send security patches to as many mobile devices as possible at a considerable speed and lower cost in the mobile network. It is a reasonable, effective, and secure method to reduce the damages mobile viruses may cause.

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Ukoette Jeremiah Ekah and Chibuzo Emeruwa. "A comparative assessment of GSM and UMTS Networks." World Journal of Advanced Research and Reviews 13, no. 1 (January 30, 2022): 187–96. http://dx.doi.org/10.30574/wjarr.2022.13.1.0011.

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It is common knowledge that the transition of mobile networks from one generation to another is basically for the improvement in the network’s Quality of Service (QoS). Bearing this in mind, we will assumme that the Universal Mobile Telecommunication System (UMTS) will outperform the Global System for Mobile Communication (GSM), hence, the motivation to conduct this study in Calabar, Nigeria, for four mobile networks; MTN, Airtel, Globacom and 9mobile. With the aid of a TEMS investigation software installed in a laptop, a measurement campaign was carried out and log files collected, with focus on Call Setup Success Rate (CSSR), Dropped Call Rate (DCR), Handover Success Rate (HOSR), Call Setup Time (CST), network coverage and network quality. The collected data was analyzed with the aid of a TEMS discovery software. The analyzed data for each Key Performance Indicator (KPI) was compared with the minimum benchmark of the telecommunications regulatory body, the Nigerian Communication Commission (NCC). Result reveal that there was no outright improvement in the QoS and there was fluctuation in the QoS provided by the network operators. We therefore conclude that the network operators, either did not make accurate planning before installing their base stations or do not optimize their networks frequently and this led to poor QoS in most cases.

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Murugan, S., and Dr M. Jeyakarthic. "Optimal Deep Neural Network based Classification Model for Intrusion Detection in Mobile Adhoc Networks." Journal of Advanced Research in Dynamical and Control Systems 11, no. 10-SPECIAL ISSUE (October 31, 2019): 1374–87. http://dx.doi.org/10.5373/jardcs/v11sp10/20192983.

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Botella-Mascarell, Carmen, Joaquin Perez, Juan Soria, and Sandra Roger. "On the Use of Composite Indicators for Mobile Communications Network Management in Smart Sustainable Cities." Applied Sciences 11, no. 1 (December 27, 2020): 181. http://dx.doi.org/10.3390/app11010181.

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Beyond 5G networks will be fundamental towards enabling sustainable mobile communication networks. One of the most challenging scenarios will be met in ultra-dense networks that are deployed in densely populated areas. In this particular case, mobile network operators should benefit from new assessment metrics and data science tools to ensure an effective management of their networks. In fact, incorporating architectures allowing a cognitive network management framework could simplify processes and enhance the network’s performance. In this paper, we propose the use of composite indicators based on key performance indicators both as a tool for a cognitive management of mobile communications networks, as well as a metric which could successfully integrate more advanced user-centric measurements. Composite indicators can successfully synthesize and integrate large amounts of data, incorporating in a single index different metrics selected as triggers for autonomous decisions. The paper motivates and describes the use of this methodology, which is applied successfully in other areas with the aim of ranking metrics to simplify complex realities. A use case that is based on a universal mobile telecommunications system network is analyzed, due to technology simplicity and scalability, as well as the availability of key performance indicators. The use case focuses on analyzing the fairness of a network over different coverage areas as a fundamental metric in the operation and management of the networks. To this end, several ranking and visualization strategies are presented, providing examples of how to extract insights from the proposed composite indicator.

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Prakash, Arun, Rajesh Verma, Rajeev Tripathi, and Kshirasagar Naik. "Extended Mobile IPv6 Route Optimization for Mobile Networks in Local and Global Mobility Domain." International Journal of Mobile Computing and Multimedia Communications 2, no. 2 (April 2010): 1–17. http://dx.doi.org/10.4018/jmcmc.2010040101.

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Network mobility (NEMO) route optimization support is strongly demanded in next generation networks; without route optimization the mobile network (e.g., a vehicle) tunnels all traffic to its Home Agent (HA). The mobility may cause the HA to be geographically distant from the mobile network, and the tunneling causes increased delay and overhead in the network. It becomes peculiar in the event of nesting of mobile networks due to pinball routing, for example, a Personal Area Network (PAN) inside a vehicle. The authors propose an Extended Mobile IPv6 route optimization (EMIP) scheme to enhance the performance of nested mobile networks in local and global mobility domain. The EMIP scheme is based on MIPv6 route optimization and the root Mobile Router (MR) performs all the route optimization tasks on behalf of all active Mobile Network Nodes (MNNs). Thus, the network movement remains transparent to sub MRs and MNNs and modifies only MRs and MNNs leaving other entities untouched and is more efficient than the Network Mobility Basic Support protocol (NEMO BS). The authors carried out an extensive simulation study to evaluate the performance of EMIP.

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Kim, Dae-Young, Dae-sik Ko, and Seokhoon Kim. "Network Access Control for Location-Based Mobile Services in Heterogeneous Wireless Networks." Mobile Information Systems 2017 (2017): 1–10. http://dx.doi.org/10.1155/2017/6195024.

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Recent advances in information communication technology and software have enabled mobile terminals to employ various capabilities as a smartphone. They adopt multiple interfaces for wireless communication and run as a portable computer. Mobile services are also transferred from voice to data. Mobile terminals can access Internet for data services anytime anywhere. By using location-based information, improved mobile services are enabled in heterogeneous networks. In the mobile service environment, it is required that mobile terminals should efficiently use wireless network resources. In addition, because video stream becomes a major service among the data services of mobile terminals in heterogeneous networks, the necessity of the efficient network access control for heterogeneous wireless networks is raised as an important topic. That is, quality of services of the location-based video stream is determined by the network access control. Therefore, this paper proposes a novel network access control in the heterogeneous wireless networks. The proposed method estimates the network status with Naïve Bayesian Classifier and performs network access control according to the estimated network status. Thus, it improves data transmission efficiency to satisfy the quality of services. The efficiency of the proposed method is validated through the extensive computer simulation.

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Tkachov, Vitalii, Andriy Kovalenko, Heorhii Kuchuk, and Iana Ni. "Method of ensuring the survivability of highly mobile computer networks." Advanced Information Systems 5, no. 2 (June 22, 2021): 159–65. http://dx.doi.org/10.20998/2522-9052.2021.2.24.

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The article discusses the features of the functioning of mobile computer networks based on small-sized aircraft (highly mobile computer networks). It is shown that such networks, in contrast to stationary or low-mobile ones, have a low level of survivability in case of local damage to their nodes. The purpose of the article is to develop a method for ensuring the survivability of highly mobile computer networks under conditions of destructive external influences, which leads to local destruction of network nodes or links between them, using the method of assessing survivability at all stages of network functioning, by changing the main function to implement all available strategies for the functioning of the network when determining the critical values of the integrity of the network and its ability to perform at least one of the available functions. The results obtained allow: to continue the development of theoretical research in the development of strategies for managing highly mobile computer networks in extreme situations; to develop an applied solution to ensure the survivability of highly mobile computer networks by building multifunctional or redundant structures, increasing the value of their redundancy. The studies allow us to conclude that the proposed method can be used at the design stages of highly mobile computer networks, characterized by increased survivability and capable of functioning in conditions of multiple local damages without catastrophic destructive consequences for the network structure.

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Onnela, J. P., J. Saramäki, J. Hyvönen, G. Szabó, D. Lazer, K. Kaski, J. Kertész, and A. L. Barabási. "Structure and tie strengths in mobile communication networks." Proceedings of the National Academy of Sciences 104, no. 18 (April 24, 2007): 7332–36. http://dx.doi.org/10.1073/pnas.0610245104.

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Electronic databases, from phone to e-mails logs, currently provide detailed records of human communication patterns, offering novel avenues to map and explore the structure of social and communication networks. Here we examine the communication patterns of millions of mobile phone users, allowing us to simultaneously study the local and the global structure of a society-wide communication network. We observe a coupling between interaction strengths and the network's local structure, with the counterintuitive consequence that social networks are robust to the removal of the strong ties but fall apart after a phase transition if the weak ties are removed. We show that this coupling significantly slows the diffusion process, resulting in dynamic trapping of information in communities and find that, when it comes to information diffusion, weak and strong ties are both simultaneously ineffective.

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Gabilondo, Álvaro, Zaloa Fernández, Roberto Viola, Ángel Martín, Mikel Zorrilla, Pablo Angueira, and Jon Montalbán. "Traffic Classification for Network Slicing in Mobile Networks." Electronics 11, no. 7 (March 30, 2022): 1097. http://dx.doi.org/10.3390/electronics11071097.

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Network slicing is a promising technique used in the smart delivery of traffic and can satisfy the requirements of specific applications or systems based on the features of the 5G network. To this end, an appropriate slice needs to be selected for each data flow to efficiently transmit data for different applications and heterogeneous requirements. To apply the slicing paradigm at the radio segment of a cellular network, this paper presents two approaches for dynamically classifying the traffic types of individual flows and transmitting them through a specific slice with an associated 5G quality-of-service identifier (5QI). Finally, using a 5G standalone (SA) experimental network solution, we apply the radio resource sharing configuration to prioritize traffic that is dispatched through the most suitable slice. The results demonstrate that the use of network slicing allows for higher efficiency and reliability for the most critical data in terms of packet loss or jitter.

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Choi, Sang-Il, Ji-In Kim, and Seok-Joo Koh. "Network-based Mobility Control in Mobile LISP Networks." KIPS Transactions:PartC 18C, no. 5 (October 31, 2011): 339–42. http://dx.doi.org/10.3745/kipstc.2011.18c.5.339.

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Banchs, Albert, Gustavo de Veciana, Vincenzo Sciancalepore, and Xavier Costa-Perez. "Resource Allocation for Network Slicing in Mobile Networks." IEEE Access 8 (2020): 214696–706. http://dx.doi.org/10.1109/access.2020.3040949.

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Palanisamy, B., N. Karthik, K. Chandrakumar, K. Thirunavukkarasu, and R. Jayasudha. "Improving Network Security in Mobile Ad Hoc Networks." Journal of Computational and Theoretical Nanoscience 16, no. 5 (May 1, 2019): 2299–301. http://dx.doi.org/10.1166/jctn.2019.7888.

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Yang, Yinying, Mirela I. Fonoage, and Mihaela Cardei. "Improving network lifetime with mobile wireless sensor networks." Computer Communications 33, no. 4 (March 2010): 409–19. http://dx.doi.org/10.1016/j.comcom.2009.11.010.

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VikramPhaneendra, S., Sreenivasulu T, and B. Jalaja Kumari. "Identifying Stable Network in Mobile Ad-Hoc Networks." International Journal of Computer Applications 43, no. 18 (April 30, 2012): 22–25. http://dx.doi.org/10.5120/6204-8761.

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Chen, Chi-Yuan, Fan-Hsun Tseng, Chin-Feng Lai, and Han-Chieh Chao. "Network planning for mobile multi-hop relay networks." Wireless Communications and Mobile Computing 15, no. 7 (July 10, 2013): 1142–54. http://dx.doi.org/10.1002/wcm.2396.

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Qi Xu, Deyun Gao, Huachun Zhou, Bohao Feng, and Taixin Li. "OpenNSP: Open Network Service Provision for Mobile Networks." Research Briefs on Information and Communication Technology Evolution 3 (May 15, 2017): 42–52. http://dx.doi.org/10.56801/rebicte.v3i.43.

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In recent years, many innovative techniques are emerged for satisfying various user requirements,such as Software Definition Network (SDN) and Network Function Virtualization (NFV). However,the current solutions for network service provision still lack enough flexibility and openness thatresult in high expenditures and complexity. Thus, we propose an Open Network Service Provision(OpenNSP) solution in this paper, aiming to address the multi-domain problems of service functionchain outsourcing for mobile networks. Particularly, OpenNSP is based on IETF hierarchical servicefunction chaining (hSFC) architecture to implement service chains hierarchically in multi-domainnetworks comprising operator network and cloud datacenters. It outsources service chains, which isusually located in SGi-LAN, to the public clouds, enabling fast, flexible and cost-effective networkservice provision. Besides, OpenNSP achieves the programmable service function placement andchaining by the integration of SDN and NFV. Much work has been done, and the experiment resultsconfirm its feasibility and flexibility.

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Lorincz, Josip, Ivica Cubic, and Toncica Matijevic. "Adaptive and Resilient Solutions for Energy Savings of Mobile Access Networks." International Journal of Adaptive, Resilient and Autonomic Systems 5, no. 3 (July 2014): 82–102. http://dx.doi.org/10.4018/ijaras.2014070105.

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Continuous development and evolution of mobile communications toward end user expectations has led to heterogeneous mobile networks in the most general sense of the word. The mixture of core network infrastructures and radio access technologies, due to the arrival of new technologies while older ones are still used and not fully exploited, brings mobile operators to a complex business environment. Such a situation threatens future profit margins since the cost of running mobile networks rises with greater pace than total profit. A significant share in the total costs of running a mobile network belongs to energy consumption. Decreasing energy costs by designing hardware with low-energy consumption characteristics and site collocation is already under way, but additional sparing could be achieved through soft solutions or adaptive networks. To reduce operational costs, the crucial role will be played by the self-organizing network paradigm, featured by network management systems and operations/business support systems. In this paper, the authors provide an overview of adaptive and resilient concepts appropriate for improving the energy efficiency of mobile access networks. More precisely, they present the most promising self-organizing network solutions in the radio access and backhaul part of mobile networks, the implementation of which can bring a synergetic effect in terms of significant energy savings.

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Ramya, K. "Mobile Computing Broadband Networks." International Journal for Research in Applied Science and Engineering Technology V, no. II (February 28, 2017): 292–94. http://dx.doi.org/10.22214/ijraset.2017.2045.

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Sousa, E. S. "CDMA Mobile Communication Networks." Journal of Communication and Information Systems 9, no. 1 (December 30, 1994): 5–26. http://dx.doi.org/10.14209/jcis.1994.1.

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Alexander, Tom, Wojciech Mazurczyk, Amitabh Mishra, and Alberto Perotti. "Mobile Communications and Networks." IEEE Communications Magazine 57, no. 1 (January 2019): 42. http://dx.doi.org/10.1109/mcom.2019.8613272.

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Alexander, Tom, Wojciech Mazurczyk, Amitabh Mishra, and Alberto Perotti. "Mobile Communications and Networks." IEEE Communications Magazine 57, no. 4 (April 2019): 94. http://dx.doi.org/10.1109/mcom.2019.8703472.

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Alexander, Tom, Wojciech Mazurczyk, Amitabh Mishra, and Alberto Perotti. "Mobile Communications and Networks." IEEE Communications Magazine 57, no. 9 (September 2019): 112. http://dx.doi.org/10.1109/mcom.2019.8847237.

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Alexander, Tom, Wojciech Mazurczyk, Amitabh Mishra, and Alberto Perotti. "Mobile Communications and Networks." IEEE Communications Magazine 57, no. 12 (December 2019): 37. http://dx.doi.org/10.1109/mcom.2019.8930823.

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Alexander, Tom, Wojciech Mazurczyk, Amitabh Mishra, and Alberto Perotti. "Mobile Communications and Networks." IEEE Communications Magazine 58, no. 3 (March 2020): 54. http://dx.doi.org/10.1109/mcom.2020.9040263.

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Alexander, Tom, Wojciech Mazurczyk, Amitabh Mishra, and Alberto Perotti. "Mobile Communications and Networks." IEEE Communications Magazine 58, no. 5 (May 2020): 48. http://dx.doi.org/10.1109/mcom.2020.9112741.

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Alexander, Thomas, Wojciech Mazurczyk, Amitabh Mishra, and Alberto Perotti. "Mobile Communications and Networks." IEEE Communications Magazine 58, no. 7 (July 2020): 12. http://dx.doi.org/10.1109/mcom.2020.9161987.

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Alexander, Tom, Ilker Demirkol, Amitabh Mishra, and Alberto Perotti. "Mobile Communications and Networks." IEEE Communications Magazine 58, no. 9 (September 2020): 73. http://dx.doi.org/10.1109/mcom.2020.9214392.

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Kolios, Panayiotis, Vasilis Friderikos, and Katerina Papadaki. "Future Wireless Mobile Networks." IEEE Vehicular Technology Magazine 6, no. 1 (March 2011): 24–30. http://dx.doi.org/10.1109/mvt.2010.939905.

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Huber, J. F. "Mobile next-generation networks." IEEE Multimedia 11, no. 1 (January 2004): 72–83. http://dx.doi.org/10.1109/mmul.2004.1261110.

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Alwan, A., R. Bagrodia, N. Bambos, M. Gerla, L. Kleinrock, J. Short, and J. Villasenor. "adaptive mobile multimedia networks." IEEE Personal Communications 3, no. 2 (April 1996): 34–51. http://dx.doi.org/10.1109/98.490751.

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Yelland, Mark. "Fraud in mobile networks." Computer Fraud & Security 2013, no. 3 (March 2013): 5–9. http://dx.doi.org/10.1016/s1361-3723(13)70027-7.

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